Study on Woven Fabric Texture Based on Fourier Transform and Gabor Transform

Li Qing Li; Ting Ting Shan; Le Xue; Jun Wang; Xia Chen

doi:10.4028/www.scientific.net/KEM.671.369

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HomeKey Engineering MaterialsKey Engineering Materials Vol. 671Study on Woven Fabric Texture Based on Fourier...

Study on Woven Fabric Texture Based on Fourier Transform and Gabor Transform

Abstract:

Woven fabric texture was periodic and complex, the woven fabric texture analysis method was based on Fourier transform and Gabor transform. Firstly the frequency range of woven fabric texture was obtained by using the Fourier Transform method, and the influence on fabric frequency of image resolution and fabric density was analyzed. Then the main parameters of Gabor filter was confirmed by the woven fabric texture frequency, and the sub-images which contain different texture information were obtained after the woven fabric images were decomposed and fused in different scales and directions using the Gabor filters. Finally the main texture enhancement method, the main texture elimination method, the direntional texture analysis method and extraessential texture enhancement method were discussed. The experiment proved that this method would be a powerful tool in the application of texture analysis.

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Periodical:

Key Engineering Materials (Volume 671)

Pages:

369-377

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.671.369

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Online since:

November 2015

Authors:

Li Qing Li*, Ting Ting Shan, Le Xue, Jun Wang, Xia Chen

Keywords:

Fabric Texture, Fourier Transform, Gabor Transform, Image Decomposition, Image Fusion

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* - Corresponding Author

References

[1] SUN Jun-Ding, MA Yuan-Yuan. Summary of Texture Feature Researth[J]. Computer system application, 2010, 19(6): 245-250.

Google Scholar

[2] LIU Xiao-Mi. Summary of Texture Research[J]. Measurement and Control Technology, 2008, 27(5): 4-9.

Google Scholar

[3] YAO Fang, LI Li-Qing. Fabric Defect Detection Based on Adaptive Wavelet of Three-tier Decomposition[J]. Textile Science and Technology, 2010, (1): 63-66.

Google Scholar

[4] LI Li-Qing, HUANG Xiu-bao. Study on Computer Vision-based Automatic Detection of Fabric Defects[D]. Donghua University, 2003. 46-47.

Google Scholar

[5] HAN Runping, ZHANG Lingmin. Fabric Defect detection method based on Gabor filters mask [J]. Global Congress on Intelligent Systems, 2009, 184-188.

DOI: 10.1109/gcis.2009.356

Google Scholar